1. Field of the Invention
The present invention relates, generally, to a method of predicting maintenance of an apparatus, and, more particularly, to a method of online predicting maintenance of an apparatus.
2. Description of the Related Art
With the improvement of semiconductor chip technology, the feature size is keeping decreased from 250 nm to 65 nm, even less than 45 nm; while the size of silicon wafer is increased from 200 mm to 300 mm. As a result, the cost of each individual wafer is increasing, and the requirements to the semiconductor wafer manufacturing process are stricter. The semiconductor manufacturing comprises many process steps including deposition, photolithography and etching process, etc., wherein the etching process is more complex, because the state of plasma and other parameters during the etching process have direct influence upon the result of etching process. With the feature size decreasing, it is more and more important to control and monitor these parameters mentioned above. To meet the above requirements, the Advanced Process Control (APC) technology has been developed.
APC technology mainly includes three aspects, namely malfunction diagnosis and classification, malfunction prediction, and feedback control.
As for the maintenance of the apparatus, the conventional method is to estimate the time when a maintenance operation has to be performed by experience, and carrying out periodic maintenance. In this method, in a testing stage of the apparatus, the time when a maintenance operation has to be performed is estimated by the experimental and processing results so as to control the use and maintenance of the apparatus. Generally, the dry clean period of the apparatus and the replacement period of components are obtained using the determined radio frequency loading time in the apparatus. Such a method may be applied to a process with feature size having larger width because of lower requirement to accuracy. However it is difficult to use in a process wherein feature size is less than 90 nm.
Using this method, the apparatus maintenance period can be estimated only by experience, and it is difficult to predict which part of the apparatus needs to be maintained accurately and quantitatively. The preventive maintenance period may vary with the conditions such as specific process and aging of the apparatus changing, and if the experiential data is varied, the process and the result will be also varied accordingly. Very long period will result in that the change in the working condition in process causes the change in processing result, thus leading to the degrading of wafer quality, and reducing the throughput rate; on the other hands, very short period will lead to frequent maintenance, which will affect disadvantageously regular wafer process, and result in wasting time and decreasing of efficiency.
Another conventional method of predicting the maintenance requirement of the apparatus is using an additional sensor to detect the process, generally, said sensor includes VI probe (radio frequency voltage, current probe) or FTIR (Fourier transform infrared spectroscopy), etc. In the process, these sensors are mainly used to detect progress of process, which can predict maintenance requirement such as dry clean and component replacement by the value of plasma or other processing condition parameters.
The disadvantages of the conventional methods mentioned above are that the cost of apparatus is increased, and the mechanical design of apparatus is needed to change so as to satisfy the additional sensor.